1. Field of the Invention
The present invention relates generally to the field of processor-based imaging, and, more particularly, to optimizing image operations in registration applications using GPUs.
2. Description of the Related Art
Medical imaging has become a vital component for numerous medical applications, ranging from diagnostics and planning to consummation and evaluation of surgical and radiotherapeutical procedures. A vast number of imaging modalities are currently used, including two-dimensional modalities (e.g., x-ray, angiography and ultrasound (“US”)) and three-dimensional modalities (e.g., computed tomography (“CT”), magnetic resonance tomography (“MRT”) and positron emission tomography (“PET”)).
Medical professionals often acquire more than one image of a patient at different points of time and/or by means of different imaging modalities. The variety of images often provide complementary information. Thus, it is generally desirable to merge the data from the various images. This is known as data fusion. Data fusion may provide the physician with more information than if the physician analyzed each image by itself. Further, data fusion may exploit the available data to a maximum degree, thereby reducing the overall number of images needed to be acquired and potentially lowering operating costs for a medical provider and inconveniences (e.g., exposure to radiation) for a patient. The first step of data fusion is typically registration, which refers to the process of bringing different images into spatial alignment.
Digital medical images, especially three-dimensional volumetric data, can easily reach hundreds of megabytes in size (say 500 slices of 512×512 images with 16-bit pixels equals 260 MB). Therefore, the registration of digital medical images can be computationally quite expensive.